IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i14p7822-d593755.html
   My bibliography  Save this article

Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem

Author

Listed:
  • Andrés Martínez-Reyes

    (Operations and Supply Chain Management Research Group, Escuela Internacional de Ciencias Económicas y Administrativas, Universidad de La Sabana Km 7 Autopista Norte de Bogotá, D.C., Chía 250001, Colombia)

  • Carlos L. Quintero-Araújo

    (Operations and Supply Chain Management Research Group, Escuela Internacional de Ciencias Económicas y Administrativas, Universidad de La Sabana Km 7 Autopista Norte de Bogotá, D.C., Chía 250001, Colombia)

  • Elyn L. Solano-Charris

    (Operations and Supply Chain Management Research Group, Escuela Internacional de Ciencias Económicas y Administrativas, Universidad de La Sabana Km 7 Autopista Norte de Bogotá, D.C., Chía 250001, Colombia)

Abstract

The coronavirus disease 2019, known as COVID-19, has generated an imminent necessity for personal protective equipment (PPE) that became essential for all populations and much more for health centers, clinics, hospitals, and intensive care units (ICUs). Considering this fact, one of the main issues for cities’ governments is the distribution of PPE to ICUs to ensure the protection of medical personnel and, therefore, the sustainability of the health system. Aware of this challenge, in this paper, we propose a simheuristic approach for supplying personal protective equipment to intensive care units which is based on the location-routing problem (LRP). The objective is to provide decision makers with a decision support tool that considers uncertain demands, distribution cost, and reliability in the solutions. To validate our approach, a case study in Bogotá, Colombia was analyzed. Computational results show the efficiency of the usage of alternative safety stock policies to face demand uncertainty in terms of both expected stochastic costs and reliabilities.

Suggested Citation

  • Andrés Martínez-Reyes & Carlos L. Quintero-Araújo & Elyn L. Solano-Charris, 2021. "Supplying Personal Protective Equipment to Intensive Care Units during the COVID-19 Outbreak in Colombia. A Simheuristic Approach Based on the Location-Routing Problem," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7822-:d:593755
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/14/7822/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/14/7822/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joaquín Pacheco & Manuel Laguna, 2020. "Vehicle routing for the urgent delivery of face shields during the COVID-19 pandemic," Journal of Heuristics, Springer, vol. 26(5), pages 619-635, October.
    2. Albareda-Sambola, Maria & Fernandez, Elena & Laporte, Gilbert, 2007. "Heuristic and lower bound for a stochastic location-routing problem," European Journal of Operational Research, Elsevier, vol. 179(3), pages 940-955, June.
    3. Nadizadeh, Ali & Hosseini Nasab, Hasan, 2014. "Solving the dynamic capacitated location-routing problem with fuzzy demands by hybrid heuristic algorithm," European Journal of Operational Research, Elsevier, vol. 238(2), pages 458-470.
    4. Helena R. Lourenço & Olivier C. Martin & Thomas Stützle, 2010. "Iterated Local Search: Framework and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 363-397, Springer.
    5. Nagy, Gabor & Salhi, Said, 2007. "Location-routing: Issues, models and methods," European Journal of Operational Research, Elsevier, vol. 177(2), pages 649-672, March.
    6. Ubaid Illahi & Mohammad Shafi Mir, 2021. "Maintaining efficient logistics and supply chain management operations during and after coronavirus (COVID-19) pandemic: learning from the past experiences," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11157-11178, August.
    7. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    8. Rabbani, M. & Heidari, R. & Yazdanparast, R., 2019. "A stochastic multi-period industrial hazardous waste location-routing problem: Integrating NSGA-II and Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 272(3), pages 945-961.
    9. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
    10. Salhi, Said & Rand, Graham K., 1989. "The effect of ignoring routes when locating depots," European Journal of Operational Research, Elsevier, vol. 39(2), pages 150-156, March.
    11. Zare Mehrjerdi, Yahia & Nadizadeh, Ali, 2013. "Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands," European Journal of Operational Research, Elsevier, vol. 229(1), pages 75-84.
    12. Prodhon, Caroline & Prins, Christian, 2014. "A survey of recent research on location-routing problems," European Journal of Operational Research, Elsevier, vol. 238(1), pages 1-17.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    2. Zhang, Ying & Qi, Mingyao & Lin, Wei-Hua & Miao, Lixin, 2015. "A metaheuristic approach to the reliable location routing problem under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 90-110.
    3. Ben Mohamed, Imen & Klibi, Walid & Sadykov, Ruslan & Şen, Halil & Vanderbeck, François, 2023. "The two-echelon stochastic multi-period capacitated location-routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 645-667.
    4. Ahmadi-Javid, Amir & Amiri, Elahe & Meskar, Mahla, 2018. "A Profit-Maximization Location-Routing-Pricing Problem: A Branch-and-Price Algorithm," European Journal of Operational Research, Elsevier, vol. 271(3), pages 866-881.
    5. M. Tadaros & A. Migdalas, 2022. "Bi- and multi-objective location routing problems: classification and literature review," Operational Research, Springer, vol. 22(5), pages 4641-4683, November.
    6. Zhuo Sun & Ni Yan & Yining Sun & Haobin Li, 2019. "Location-Routing Optimization with Split Demand for Customer Self-Pickup via Data Analysis and Heuristics Search," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-24, December.
    7. Liu, Yubin & Ye, Qiming & Escribano-Macias, Jose & Feng, Yuxiang & Candela, Eduardo & Angeloudis, Panagiotis, 2023. "Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    8. Sahar Validi & Arijit Bhattacharya & P. J. Byrne, 2020. "Sustainable distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routing model," Annals of Operations Research, Springer, vol. 290(1), pages 191-222, July.
    9. Zhu, Stuart X. & Ursavas, Evrim, 2018. "Design and analysis of a satellite network with direct delivery in the pharmaceutical industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 190-207.
    10. Danışment Vural & Robert F. Dell & Erkan Kose, 2021. "Locating unmanned aircraft systems for multiple missions under different weather conditions," Operational Research, Springer, vol. 21(1), pages 725-744, March.
    11. Bergmann, Felix M. & Wagner, Stephan M. & Winkenbach, Matthias, 2020. "Integrating first-mile pickup and last-mile delivery on shared vehicle routes for efficient urban e-commerce distribution," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 26-62.
    12. Jaller, Miguel & Pahwa, Anmol, 2023. "Coping with the Rise of E-commerce Generated Home Deliveries through Innovative Last-mile Technologies and Strategies," Institute of Transportation Studies, Working Paper Series qt5t76x0kh, Institute of Transportation Studies, UC Davis.
    13. Prodhon, Caroline & Prins, Christian, 2014. "A survey of recent research on location-routing problems," European Journal of Operational Research, Elsevier, vol. 238(1), pages 1-17.
    14. Younes Rahmani & Wahiba Ramdane Cherif-Khettaf & Ammar Oulamara, 2016. "The two-echelon multi-products location-routing problem with pickup and delivery: formulation and heuristic approaches," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 999-1019, February.
    15. Janjevic, Milena & Merchán, Daniel & Winkenbach, Matthias, 2021. "Designing multi-tier, multi-service-level, and multi-modal last-mile distribution networks for omni-channel operations," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1059-1077.
    16. Michael Schneider & Michael Drexl, 2017. "A survey of the standard location-routing problem," Annals of Operations Research, Springer, vol. 259(1), pages 389-414, December.
    17. Wang, Congke & Liu, Yankui & Yang, Guoqing, 2023. "Adaptive distributionally robust hub location and routing problem with a third-party logistics strategy," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    18. Pourya Pourhejazy & Oh Kyoung Kwon, 2016. "The New Generation of Operations Research Methods in Supply Chain Optimization: A Review," Sustainability, MDPI, vol. 8(10), pages 1-23, October.
    19. Menezes, Mozart B.C. & Ruiz-Hernández, Diego & Verter, Vedat, 2016. "A rough-cut approach for evaluating location-routing decisions via approximation algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 89-106.
    20. Bagheri Hosseini, Mozhde & Dehghanian, Farzad & Salari, Majid, 2019. "Selective capacitated location-routing problem with incentive-dependent returns in designing used products collection network," European Journal of Operational Research, Elsevier, vol. 272(2), pages 655-673.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7822-:d:593755. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.